BOL: Related items

Research Associate Bioinformatics in IISc Recruitment 2020

Tue, 23 Jun 2020 21:53:34 -0500

Research Associate Bioinformatics in IISc Recruitment 2020

Essential Qualifications: Ph.D. (Bioinformatics/ Biophysics/ Biotechnology or any other stream of biological/ physical sciences) with a minimum of two publications in reputed peer reviewed journals in the area of structural bioinformatics or biophysics or biomolecular modeling/ simulation.

Job description: Development of bioinformatics tools and algorithms/software for structure based analysis of biomolecular systems. Programmatic access to major biomolecular databases using APIs Knowledge based prediction and analysis of biomolecular structure, function and interactions. Docking/simulations for inhibitor design.

Desirable Qualifications (Research Associate/s): i) Strong computer programming skills (in Python/PERL/PHP or C++ or object oriented database management systems like MySQL etc or scripting languages under LINUX/UNIX environment).

ii) Extensive experience in computational analysis of biomolecular structure/interactions and usage of advanced biomolecular simulation softwares. iii) Adequate knowledge of major databases, webservers and softwares in the area of biomolecular structure/function and drug design. iv) Familiarity with Parallel Programming environments and experience in usage of high-end HPC clusters.

The candidates must highlight their experience in above mentioned fields/topics in their CV. Initial appointment will be for a period of 1 year, subject to extension after review of performance.

Emoluments: As per DST, GOI norms and commensurate with experience.

More at https://www.iisc.ac.in/positions-open/

Understanding Fastqc Output

Jit — Fri, 15 Apr 2016 05:47:40 -0500

Understanding Following table and graphs

Duplication level
kmer profile
per base GC content
per base N content
per base quality
per base sequence content
per sequence GC content
per sequence quality
sequence length distribution

More at http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/

Address of the bookmark: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/

ALE: a Generic Assembly Likelihood Evaluation Framework for Assessing the Accuracy of Genome and Metagenome Assemblies

Neel — Tue, 26 Apr 2016 03:38:43 -0500

Assembly Likelihood Evaluation (ALE) framework that overcomes these limitations, systematically evaluating the accuracy of an assembly in a reference-independent manner using rigorous statistical methods. This framework is comprehensive, and integrates read quality, mate pair orientation and insert length (for paired-end reads), sequencing coverage, read alignment and k-mer frequency. ALE pinpoints synthetic errors in both single and metagenomic assemblies, including single-base errors, insertions/deletions, genome rearrangements and chimeric assemblies presented in metagenomes. At the genome level with real-world data, ALE identifies three large misassemblies from the Spirochaeta smaragdinae finished genome, which were all independently validated by Pacific Biosciences sequencing. At the single-base level with Illumina data, ALE recovers 215 of 222 (97%) single nucleotide variants in a training set from a GC-rich Rhodobacter sphaeroides genome. Using real Pacific Biosciences data, ALE identifies 12 of 12 synthetic errors in a Lambda Phage genome, surpassing even Pacific Biosciences' own variant caller, EviCons. In summary, the ALE framework provides a comprehensive, reference-independent and statistically rigorous measure of single genome and metagenome assembly accuracy, which can be used to identify misassemblies or to optimize the assembly process.

More at http://www.ncbi.nlm.nih.gov/pubmed/23303509

Address of the bookmark: http://sc932.github.io/ALE/about.html

Edanchin Lab

Thu, 19 Nov 2020 08:00:07 -0600

My main topics of interest are:

The impact of non tree-like evolution such as horizontal gene transfers and hybridization on species biology
Evolution and adaptation of animals in the absence of sexual reproduction and the underlying mechanisms
Genomic signatures of adaptation to a parasitic life-style

More at https://edanchin.org/

HGA

Jit — Tue, 29 Nov 2016 07:25:53 -0600

HGA tool version 1.0 This tool helps to apply the Hierarchical Genome Assembly (HGA) method. The tool will apply: 1. Partitioning a given reads dataset into a given number of partitions. 2. Assembling each partitions using a pre-specified assembler (Velvet or SPAdes in this version) and using a given kmer size. 3. Merging all the assemblies of the partition. 4. Combining all the assemblies of the partition (using velvet with kmer value of 31). 5. Finaly, re-assembling the whole dataset with the merged contigs or the combined contigs, using a given kmer size.

https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA

Address of the bookmark: https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA

A Post-assembly genome-improvement toolkit (PAGIT) to obtain annotated genomes from contigs

Abhimanyu Singh — Fri, 12 May 2017 10:50:29 -0500

PAGIT addresses the need for software to generate high quality draft genomes. It is based on a series of programs that we developed:

ABACAS, that is able to contiguate contigs from a de novo assembly against a closely related reference.

IMAGE, an iterative approach for closing gaps in assembled genomes using mate pair information. It is able to close gaps left open by the assembler in a draft genome, even when using the same data sets as used by the original assembler.

iCORN, that enables errors in the consensus sequence to be corrected by iteratively mapping reads to the current assembly. An improved version, especially correction Pacfic Bioscience assemblies (PacBio) can be found here.

RATT, a tool to transfer the annotation from a reference genome, or an earlier assembly, onto the latest assembly.

PAGIT bundles these software and makes them more accessible for users.

Address of the bookmark: http://www.sanger.ac.uk/science/tools/pagit

SIMBA: a web tool for managing bacterial genome assembly generated by Ion PGM sequencing technology

Abhimanyu Singh — Tue, 23 May 2017 05:28:56 -0500

SIMBA, SImple Manager for Bacterial Assemblies, is a Web interface for managing assembly projects of bacterial genomes. SIMBA was created to assist bioinformaticians to assemble bacterial genomes sequenced with NextGeneration Sequencing (NGS) platforms quickly, easily and effectively. SIMBA also is open source tool, i.e., can be freely downloaded, shared and modified.

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1344-7

Address of the bookmark: http://ufmg-simba.sourceforge.net/

Bioinformatics Head (Bioinformatics Manager III), Cancer Genomics Research Laboratory at Frederick National Laboratory

Wed, 18 Aug 2021 00:19:48 -0500

Frederick National Laboratory seeking an enthusiastic, creative, and seasoned bioinformatics professional to join our leadership team and direct the exceptional Bioinformatics Group at the Cancer Genomics Research Laboratory (CGR). CGR has a diverse team of bioinformatics and computational scientists that support all areas of bioinformatics and data analysis (infrastructure, data QC, pipeline development and maintenance, data curation and sharing, methodology development, statistical analyses, machine learning approaches, and scientific interpretation).

More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&c=leidosbiomed&id=2040

Phased Human Genome Assembly !

Rahul Nayak — Mon, 08 Oct 2018 09:10:54 -0500

The new publicly available assembly (PacBio HG00733) has the fewest gaps of any human genome assembly, with more than half of the genome contained in gapless sequence at least 27 Mb long. The primary contig assembly is 2.89 Gb long and consists of 865 contigs that were assembled with PacBio data generated with the company’s Sequel® System. Using the FALCON-Unzip assembler, maternal and paternal haplotypes were resolved over more than 80% of the genome. Maternal and paternal haplotype blocks were then further phased using Hi-C technology and the FALCON-Phase methoddeveloped in collaboration with Phase Genomics. The genome was then de novo scaffolded using Phase Genomics’ Proximo Hi-C platform, resulting in the first chromosome-scale diploid assembly of a single individual accomplished with only two technologies. More specific details about the assembly are included on the PacBio blog.

The data are available using NCBI accession IDs: BioProject: (PRJNA483067), assembly: [RBJD00000000] and sequence data (SRP155659).

Additional Resources

Interactive map showcasing global initiatives underway to generate reference-quality human genome assemblies for diverse populations
BioReport Podcast on the value of ethnic-specific reference genomes
Nature Reviews Genetics paper from NHGRI: Prioritizing diversity in human genomics research
Article in The Journal of Precision Medicine: “Minority Report – Ethnic Diversity and the Real Promise for Precision Medicine”
Article in Bio-IT World: “Genomic Data Standards Are a Necessity”
NHGRI Project Award: High Quality Human and Non-Human Primate Genome Assemblies

More details are available on the PacBio website:

Blog post: Data Release: Highest-Quality, Most Contiguous Individual Human Genome Assembly to Date
Blog post: For Reference-Grade Human Genome Assemblies, SMRT Sequencing Yields Optimal Results
Webinar: Assembling High-Quality Human Reference Genomes for Global Populations
FALCON-Phase press release and article preprint
PacBio research focus webpage about Human Population Genetics

Ref: https://stockguru.com/2018/10/08/pacific-biosciences-releases-highest-quality-most-contiguous-individual-human-genome-assembly-to-date/

RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs

BioJoker — Wed, 17 Apr 2019 19:45:22 -0500

Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC: Fast and accurate reference-guided scaffolding of draft genomes. bioRxiv 2019.

RaGOO is a tool for coalescing genome assembly contigs into pseudochromosomes via minimap2 alignments to a closely related reference genome. The focus of this tool is on practicality and therefore has the following features:

Good performance. On a MacBook Pro using Arabidopsis data, pseudochromosome construction takes less than a minute and the whole pipeline with SV calling takes ~2 minutes.
Intact ordering and orienting of contigs.
Chimeric contig correction
GFF lift-over
Structural variant calling with and integrated version of Assemblytics
Confidence scores associated with the grouping, localization, and orientation for each contig.

Address of the bookmark: https://github.com/malonge/RaGOO